2782-6015 16 3 2023 1-134

RAR RUS 7-21 Lomakin Nikolay Yurova Olga Terekhov Taras Shabanov Nikita Development of a random forest ai based robo-advisor as a factor of increasing the investment activity of the population The article discusses current trends in the use of artificial intelligence in the financial market. The relevance of the study is based on active use of exchange trading robots when conducting transactions on the exchange. However, despite some “splash” in 2021, the low investment activity of the population remains an acute problem. The purpose of the work is to solve a major national economic problem: increasing the investment activity of the population of the Russian Federation, strengthening the stability of the financial sector through the active use of private investors’ funds thanks to the introduction of a reliable robo-advisor. In the course of the study, the following tasks were solved: 1) theoretical basis for increasing the investment activity of the population was investigated; 2) an analysis of the current state of financial markets was carried out and trends in the use of artificial intelligence were identified; 3) a reliable highly efficient neural-network robo-advisor was developed. The scientific novelty lies in the fact that the proposed algorithm is based on the use of the machine learning algorithm of Random Forest, which allows you to get a reliable forecast for each next hour during the exchange trading of the SiH3 futures contract. The practical significance and value is that the developed recommendations can be implemented in practice, as they are confirmed by certificates of state registration for PC software. As a result of the study, conclusions were drawn: firstly, increasing the investment activity of the population contributing to the strengthening of the stability of the financial sector is important; secondly, the use of AI systems to support decision-making by private investors plays an important role in modern conditions; thirdly, the developed algorithm based on Random Forest machine learning is proposed, which allows you to get a reliable forecast of the price of the SiH3 futures contract for each next hour, providing a yield of 17,1 % during the exchange trading day. Among the directions for further scientific research, the use of Industry 5.0 technologies should be noted. 10.18721/JE.16301 336.6 investment activity of the population sustainable development Random Forest machine learning model Deep Learning Decision Tree https://economy.spbstu.ru/article/2023.101.1/ 01.pdf

RAR RUS 22-44 Batukova Louisa Bagdasaryan Naira. Bagdasaryan Lusine. The concept of formation of a qualified manager of the economic mechanism in the paradigm of Russia's sustainable development The systemic, paradigm crisis that has engulfed civilization today determines the need for a deep qualitative reorganization of the economic and managerial mechanism of Russian society. The most important and priority task in this regard is the formation of a "corps of qualified managers". To effectively solve the problem of forming a corps of qualified managers, a deep, integrated reform of science, education and industry with access to new factors of economic growth is necessary. The most important of the subtasks here is the formation of a “Smart (intelligent, digital) university” 4.0, which, in turn, should act as an element of the scientific and technological collaboration “University-Science Research Organizations-Industry” (University-SRO-Industry). The aim of the study is to develop a concept for the formation of a qualified manager of the economic mechanism by the forces of the Russian University 4.0, which is an element of the University-SRO-Industry collaboration. The development of the topic was carried out in the system paradigm, namely, the most important provisions of the theory of systems and the system approach applied to the analysis and modeling of social systems were used. The key results containing scientific novelty and having practical significance include: Firstly, the development and refinement of a number of concepts in the system paradigm, including: “system development”, “system sustainable development”, “system functioning”, “system functional efficiency”, and others. Secondly, the development of a concept for the formation of a qualified manager of the economic mechanism of Russia by the University 4.0. The concept substantiates approaches to a radical increase in the level of scientific character of university management education. The analysis carried out and the proposed solutions open up opportunities for reforming university education in management specialties, and will also be useful for the formation of the University 4.0 development program and for the sovereignization of homeland education in general. It should be noted that for the effective implementation of the above proposals, research should be continued, firstly, in the direction of clarifying and detailing the stated provisions, and secondly, in the field of assessing the possibility of embedding the proposed models in the macro-organizational structure of the university 4.0. 10.18721/JE.16302 303,330 University 4.0 sovereign education qualified manager transforming intelligence the principle of scientific education higher education reform university education reform social system development social system functioning sustainable develop https://economy.spbstu.ru/article/2023.101.2/ 02.pdf

RAR RUS 45-62 Pletnev Dmitriy pletnev@csu.ru Kozlova Elena Degree of use of digital technologies and propensity to opportunism at Russian enterprises: results of empirical research Digitalization contributes to an increase in labor productivity, industrial growth, and in the efficiency of industrial production. The coronavirus pandemic has given an additional impetus to digitalization, and most companies around the world have realized the importance of this process for the resilience of the organization in the face of constant change. A significant role in this process is played by the state, which determines the priority areas of digital transformation. At the same time, the implementation of state programs in the field of digitalization may be hindered by a shortage of personnel. The article provides an analysis of studies of the impact of digital transformation on the efficiency of enterprises and industries, which note the positive influence of digitalization on the country’s economy. The digitalization process covers all key areas of the company’s activities: production, finances, personnel management, logistics, industrial and information security. The intensive transition to technological independence in the face of sanctions pressure contributes to the acceleration of the digitalization process and the influx of investments in digital and technological development. One of the limiting factors of digital transformation is behavioral opportunism in enterprises. Resistance to change on the part of staff, caused by a low level of digital competencies and fear of change, leads to a significant slowdown in the digitalization process. The purpose of the article is to assess the degree of use of digital technologies and the propensity to opportunism in Russian enterprises. Based on the author’s methodology, the study assessed the level of digitalization in work and daily activities based on the results of a survey of employees of Russian enterprises. The analysis of differences in the degree of use of digital technologies among different groups of workers was carried out. Differences in the level of behavioral opportunism at Russian enterprises for employees with varying degrees of use of digital technologies in work and daily activities are revealed. An industry analysis of the degree of use of digital technologies in Russian enterprises was carried out. Among the industries with the highest level of digital technology proficiency, workers in construction and engineering, banking, telecommunications and the electric power industry were noted. It was revealed that behavioral opportunism at Russian enterprises is influenced by the degree of ownership and use of digital technologies by employees in work and in everyday life. As the indicators characterizing the use of digital technologies grow, the level of behavioral opportunism decreases. Directions for further research are related to improving the methodology and developing recommendations for reducing the level of behavioral opportunism at Russian enterprises in the context of digitalization. 10.18721/JE.16303 331.44 digitalization digital technologies behavioral opportunism willingness to opportunism digital competencies IT https://economy.spbstu.ru/article/2023.101.3/ 03.pdf

RAR RUS 63-79 Balog Mikhail V-1094-2019 56968223000 0000-0002-0941-6358 Peter the Great St.Petersburg Polytechnic University Babkin Alexander babkin@spbstu.ru

Russia, 195251, St.Petersburg, Polytechnicheskaya, 29

Information space security as a regional economic security factor: assessment tool The ambiguous impact of modern information and communication technologies on the economic and social environment actualizes attention to the information aspects of economic security. The purpose of the work is to develop and test a methodology for assessing the security of the information space as a factor in the economic security of the region. Within the framework of this study, such methods as comparative analysis, typology, system method, methods of statistical analysis, index and rating methods, correlation analysis were used. Analysis and systematization of the definitions of the information security concept and research approaches to measuring this phenomenon, as well as the development of a methodology for assessing the security of the information space of regions and testing of this toolkit, led to a number of conclusions. Firstly, the security of the information space is defined as one of the significant factors in the economic security of the region. An integrated approach to the interpretation of the concept of information security is identified as a universal methodological tool that combines both technical and socially determined (cultural, historical, political, legal, financial, etc.) aspects of this issue. The developed index-rating methodology for assessing the security of the information space makes it possible to assess the likelihood of economic security threats that are informational in nature by studying the state of the digital infrastructure, the information openness of organizations and institutions, the protection of users from cyber threats, digital and financial literacy of the population. Secondly, there is no noticeable relationship between most information security components (the average level of connectivity was found only between the digital infrastructure and the information openness of organizations and institutions). This situation indicates that ensuring information security in the context of digitalization of various spheres of life is carried out spontaneously and requires greater coordination. Thirdly, inter-regional disparities in the development of digital and subject (financial) competencies of the population necessary to ensure information security are higher than similar disproportions in other components of information security (digital infrastructure, the availability of websites in organizations and institutions, and the use of anti-virus software by users). In addition, the modules of digital and financial competencies showed the worst results in terms of the number of regions that have an unsatisfactory level of information security in the relevant aspects. Summing up the results of the study, there is a noticeable need for systematic approach in the implementation of information security management policy at the regional level. The proportional development of all components of information security will increase the efficiency of the use of resources allocated for this and ensure the high quality of information space security. Further research within the framework of this issue will be aimed at clarifying the indicators of information security diagnostics and methods for their regulation. 10.18721/JE.16304 332.142 information security economic security region digital infrastructure information openness cyber threats digital literacy financial literacy https://economy.spbstu.ru/article/2023.101.4/ 04.pdf

RAR RUS 80-91 Nedosekin Alexei Generalova Anna Malyukov Yuri Abdulaeva Zinaida Assessment of the economic sustainability of light industry enterprises by fuzzy-logical methods The impact of the events of recent years on the Russian economy determines the course for the restoration and development of production in various industries. The light industry is included in the pool of industries whose work is aimed not only at retail consumption, but also at ensuring the country’s defense capability. The purpose of the article is to assess the economic sustainability of light industry enterprises using fuzzy-logical methods. The assessment is carried out in two sections: a) international manufacturing companies listed on the stock markets; b) Russian industry companies in the form of joint-stock companies. Methods. A fuzzy logic matrix aggregate calculator (MAC) was used for stability analysis. For linguistic normalization of factor levels, the Nedosekin–Frolov method was used. Since international and Russian data differ significantly in relative terms, it was decided to introduce two industry sections in the analysis: international (DB) and domestic (DB_RU), which gives two sets of linguistic normalizing classifiers for analysis. Results. Based on the results of the analysis, it can be seen that 2020 (the COVID-19 epidemic) had a rather serious impact on international companies, but did not turn out to be fatal for them (resilience was restored, in most cases, within 1 year). This analysis made it possible to determine linguistic standards for assessing the economic sustainability of light industry enterprises. The level of economic stability of Russian light industry enterprises was calculated, which showed that domestic companies cannot boast of economic sustainability in principle, and here, first of all, it is necessary to note low labor productivity, which makes domestic light industry companies uncompetitive, dooming them to lifelong localization in the borders of the Russian Federation. There is a clear demand for state intervention in sectoral economic processes, despite the fact that this is completely contrary to the liberal market paradigm. The main directions of intervention are formulated: supplier factoring, leasing of new equipment at a non-bank interest rate, reverse industrial mortgage of worn-out equipment. Conclusion. MAC technology provides ample opportunities for express assessment of enterprises and industries. However, for the purposes of a refined assessment of economic sustainability, it is necessary to move to more complex modeling and analysis technologies (for example, to a 4x6 strategic matrix). 10.18721/JE.16305 338.2 economic stability (resilience) adverse impacts matrix aggregate calculator (MAC) linguistic normalization balanced scorecard (BSC) 4x6 matrix public-private mobilization partnership https://economy.spbstu.ru/article/2023.101.5/ 05.pdf

RAR RUS 92-106 Makarov Vasiliy energy@fem.spbstu.ru Lyu Ye Evaluation of the effectiveness of investing in human capital of Chinese enterprises at the stage of transition to the "knowledge economy" The economy of the past years, when physical labor was the main driving force, by the beginning of the 21st century began to quickly turn into a knowledge-intensive innovative economy, in which the wealth of society is created mainly by mental labor, knowledge and skills of employees and leaders. Changes are associated with the widespread use of information- communication technologies, which led to the transition to the fourth industrial revolution, called Industry 4.0. This trend is spreading to the entire global economy of the 21st century, including the Chinese economy. As a result of digitalization and automation of production, the release of the labor force, as the role of the personnel remaining at enterprises is changing significantly, and its importance is increasing. The article analyzes various scientific views on the categories of “human resources” and “human capital”, reveals their relationship and differences, as well as the most common characteristics of human capital, which are especially evident in the era of the intellectualization of the economy. It is shown that human resources, that is, employees of an enterprise, are carriers of human capital, and its value is manifested through their work in the enterprise. Therefore, human capital is one of the decisive factors in the development of modern enterprises. Without investing in human resources, human capital cannot be formed: this is a necessary condition for its existence; a sufficient condition is the intellectual and social content of human resources. To ensure their sustainable development, enterprises must increase investment in human resources and strive to increase the economic return on human capital. The article examines the experience of investing in China’s individual, corporate and national human capital and draws conclusions about the presence of a general trend in the growth of such investments in the XXI century and the permanent growth of their socio-economic returns. The importance, especially for developing countries, of priority public investment in education and healthcare, in the creation of jobs for national personnel was noted. 10.18721/JE.16306 338.984 human capital human resources material capital knowledge-intensive innovative economy investments personnel of enterprises socio-economic efficiency management statistics trend correlation https://economy.spbstu.ru/article/2023.101.6/ 06.pdf

RAR RUS 107-122 Bragin Aleksey Bakhtizin Albert Implementation features of large economic models Agent-based economic models are invaluable tools for understanding complex economic systems and informed political decisions. However, the computational demands of large-scale agent-based models often require significant resources, limiting their accessibility to researchers and policymakers. This study investigates the software implementation details of historical agent-based economic models of Sweden, with a primary focus on the SVERIGE model and additional discussions on SESIM, SUNDSVAL, and MICROHUS. By examining these models and their successful implementations during periods of less capable computer hardware, we derive efficient software development approaches for modern computing systems that do not require supercomputers. These approaches include algorithmic optimizations, memory management techniques, leveraging modern hardware capabilities, and utilizing open-source libraries, frameworks, and cloud computing. Our findings demonstrate that it is possible to create large-scale agent-based economic models, which are both computationally efficient and accessible and have several important implications for the field of agent-based modeling and related disciplines. Addressing the computational bottleneck can help reduce the cost and time required for simulations, making these models more accessible to a wider range of researchers. Enabling the efficient execution of large-scale agent-based economic models can lead to better-informed policy formulation and implementation by better understanding of the potential consequences of these decisions. In addition, our study contributes to the growing movement towards open science and reproducibility in agent-based modeling by emphasizing the importance of efficient software development approaches and promoting open-source libraries and frameworks. A further direction of research in this area is the development of methods and tools for creating economic models for countries with a larger population, such as Russia. 10.18721/JE.16307 519.86 agent-based modeling economic model country model Sweden https://economy.spbstu.ru/article/2023.101.7/ 07.pdf

RAR RUS 123-134 Arteeva Valeriia Skhvediani Angi shvediani_ae@spbstu.ru Ivanova Ekaterina. Kropacheva Maria Modeling income inequality in Russia The labor market is constantly transforming under the influence of various economic factors, technological progress and demographic shifts. The assessment of income expressed in wages, as one of the key indicators of the labor market, makes it possible to determine its main trends, which can contribute to the development of effective human capital management strategies. In this paper, the authors evaluate the factors that have the greatest impact on the level of income in Russia. The study was performed using data from the Russia Longitudinal Monitoring Survey – Higher School of Economics (RLMS-HSE). Econometric modeling was performed to assess the income inequality of economic agents in Russia, depending on the level of education, region and sector of employment. The analysis used data on individuals for 2021. The sample consisted of 6325 respondents aged 18 to 97 years. A positive correlation was found between income and education level. The premium for master’s degree is 12% than the bonus paid to bachelor’s graduates who decided not to continue their studies, the premium for the degree of candidate of science is 36.3%, and Doctor of Science – 95.4%. Knowledge of a foreign language corresponds to extra 12.7% of income. The presence of regional differentiation was also confirmed. For all federal districts the bonus turned out to be negative in comparison with the federal cities: Moscow and St. Petersburg. On average, in the regions of the Far Eastern and North-Western federal districts, the wages of individuals are lower by 15 and 21%, the Urals – by 72%, the South and North Caucasian – by 70%. In addition, income significantly varies depending on employment sector. The level of income in the oil and gas, legal and chemical industries is 22, 27 and 28% higher than in the light industry. Employment in the sector of education, science and culture, social services is characterized by a negative bonus of 23, 26 and 42% relative to light industry. 10.18721/JE.16308 331.2 wages return to education labor market regional difference industry difference regression https://economy.spbstu.ru/article/2023.101.8/ 08.pdf